In our synthetic experiments, we also compare Stop&Hop with a baseline: A GRU is trained to classify irregular time series, then forced to stop at different proportions of the timeline.
This is the most basic early classifier as the halting times are always the same, disregarding the input data.
For all methods, we use the GRU-D update equations [1]} described in Section REF .
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